Although the diet of the US population meets or exceeds recommended intake levels of most essential nutrients, the quality of the diet consumed by many Americans is sub-optimal due to excessive intake of added sugars, solid fats, refined grains, and sodium. The foundations and outcomes of healthy vs. unhealthy eating habits and activity levels are complex and involve interactions between the environment and innate physiologic/genetic background. For instance, emerging research implicates chronic and acute stress responses and perturbations in the Hypothalamic-Pituitary-Adrenal axis in triggering obesity-promoting metabolic changes and poor food choices. In addition, the development of many chronic diseases, including cardiovascular disease, diabetes, cancer, asthma and autoimmune disease, results from an overactive immune response to host tissue or environmental antigens (e.g. inhaled allergens). A greater understanding is needed of the distribution of key environment-physiology interactions that drive overconsumption, create positive energy balance, and put health at risk. Researchers from the United States Department of Agriculture (USDA) Western Human Nutrition Research Center are conducting a cross-sectional "metabolic phenotyping" study of healthy people in the general population. Observational measurements include the interactions of habitual diet with the metabolic response to food intake, production of key hormones, the conversion of food into energy: the metabolism of fats, proteins, and carbohydrates, characteristics of the immune system, stress response, gut microbiota (bacteria in the intestinal tract), and cardiovascular health. Most outcomes will be measured in response to a mixed macronutrient/high fat challenge meal.
Many inflammatory responses can be modulated by specific dietary components. For example, in cardiovascular disease, macrophages and T-cells react with oxidized LDL (an endogenous modified antigen) to produce arterial plaque and subsequent blockage of coronary arteries. High intake of saturated fats (or simple sugars that drive synthesis of saturated fatty acids) may promote this inflammation by affecting macrophages and T-cells. Conversely, increased intake of omega-3 fatty acids may decrease inflammation by suppression of macrophage and T-cell pro-inflammatory activity. Long-term sub-clinical inflammation caused by intestinal bacteria has been linked to the development of Irritable Bowel Disease and related disorders. Low intake of fruits, vegetables, or whole grains or high intake of saturated fats may promote sub-clinical gut inflammation by promoting dysbiosis of the gut microbiota. Allergic asthma develops in predisposed individuals as a result of an overactive allergic-type immune response to inhaled environmental allergens. Dietary factors such as vitamin D and omega-3 fatty acids may diminish pro-inflammatory responses to environmental allergens by promoting the development of T-regulatory cells and other anti-inflammatory factors. Individual variability in chronic disease risk is well recognized. For example, why does excess adiposity lead to disease in some individuals and not others? The nature of the fat tissue rather than the abundance, may impact cross-talk with other metabolically-relevant tissues and affect disease risk. It is important to characterize healthy vs. unhealthy phenotypes across various tissues and to understand how micro- and macro-nutrients interact with molecular and metabolic pathways to support a healthy body weight. This study brings together scientists with expertise in nutritional sciences, immunology, analytical chemistry, physiology, neuroendocrinology, and behavior to understand how diet impacts metabolism and disease risk through the interplay and coordination of signals and metabolites arising from multiple organ systems. The overall objective is to characterize the phenotypic profile of participants according to their immunologic, physiologic, neuroendocrine, and metabolic responses to a dietary challenge and a physical fitness challenge by addressing the specific aims listed below. The cross-sectional study is organized into two study visits (Visit 1 and Visit 2) separated by approximately two weeks of at-home specimen and data collection. Specific Aim 1: To determine if diet quality is independently associated with systemic immune activation, inflammation, or oxidative stress differentiated by: 1. pro-inflammatory T-helper cells (Th1, Th2, and Th17 cells) and related cytokines 2. anti-inflammatory T-regulatory cells and related cytokines 3. dysbiosis of the gut microbiota and markers of gut inflammation (e.g. neopterin and myeloperoxidase) a. and to evaluate the association between dysbiosis of the gut microbiota, gut inflammation, and systemic immune activation 4. plasma metabolomic response to a mixed macronutrient challenge meal (includes diet quality and physical activity as independent variables) 5. endothelial (dys)function and vascular reactivity Specific Aim 2: To determine if a high fat/sugar challenge meal induces differential effects over time (0-6h postprandial) according to habitual diet characteristics, physical activity levels, stress levels, age, sex, or BMI on: 1. postprandial monocyte activation 2. plasma lipid metabolomic responses including non-esterified fatty acids, phospholipids, triacylglycerols, red blood cell fatty acids, endocannabinoids, bile acids, eicosanoids and related oxylipins, ceramides, sphingoid bases, and acylcarnitines 3. plasma amino acid metabolomics 4. glucose metabolism and metabolic flexibility (i.e. the ability to switch from glucose to lipid oxidation as energy sources) 5. changes in endocrinology and self-report of hunger and satiety 6. postprandial free cortisol Specific Aim 3: To determine the mechanisms of: 1. postprandial monocyte activation 2. suppression of challenge-meal induced monocyte activation by docosahexaenoic acid (DHA) (in an ex vivo experiment using a subset of samples) Specific Aim 4: To evaluate the associations between eating behavior, physical activity, and/or anthropometry and the outcomes: 1. endocrinology of hunger and satiety 2. plasma metabolomic responses 3. vulnerability and resistance to stress 4. endothelial (dys)function and vascular reactivity 5. prediction of insulin sensitivity Specific Aim 5: To determine how genetic variants affect nutrient metabolism, cardiovascular physiology, and immune function and improve understanding of how dietary factors affect these metabolic, cardiovascular and immune phenotypes.
Study Type
OBSERVATIONAL
Enrollment
393
USDA, Western Human Nutrition Research Center
Davis, California, United States
Baseline level and change in systemic immune activation following challenge meal
Number and activation level of pro-inflammatory T-helper (Th) cells (Th1, Th2 and Th17), T-regulatory (Treg) cells, and B cells will be measured in fasting blood. Monocytes and neutrophils will be measured in fasting and postprandial blood.
Time frame: 0, 0.5, 3, and 6 hours postprandial
Baseline level and change in plasma metabolome
Plasma fatty acid profiles of non-esterified fatty acids, phospholipids, triacylglycerols, red blood cell fatty acids, endocannabinoids, bile acids, eicosanoids and related oxylipins, ceramides, sphingoid bases, acylcarnitines, amino acids and other metabolites measured in response to a challenge meal.
Time frame: 0, 0.5, 3, and 6 hours postprandial
Baseline level and change in glucose metabolism
Glucose and insulin measured in response to a challenge meal.
Time frame: 0, 0.5, 3, and 6 hours postprandial
Baseline level and change in appetitive hormones
Cholecystokinin, incretins, Peptide YY 3-36, ghrelin measured in response to a challenge meal.
Time frame: 0, 0.5, 3, and 6 hours postprandial
Baseline level and change in mitogen activated protein (MAP) kinase activity
Mononuclear cells or B cells will be measured for MAP kinase activities in fasting and postprandial blood.
Time frame: 0, 0.5, 3 and 6 hours postprandial
Baseline level and change in dietary-responsive, circulating microRNA
Plasma microRNA measured in response to a challenge meal
Time frame: 0, 0.5, 3, and 6 hours postprandial
Baseline level and change in RNA transcriptome
Transcriptome RNA sequenced in whole blood
Time frame: 0, 3, and 6 hours postprandial
Genome Wide Association Study (GWAS)
DNA sequence from whole blood will be analyzed
Time frame: 0 hours (fasting)
General health
Clinical chemistry panel and complete blood count
Time frame: 0 hours (Fasting)
Anthropometrics
Height (cm), weight (kg), waist and hip circumference (cm)
Time frame: single time point
Vital signs
Blood pressure (mmHg), pulse rate (beats per minute) and temperature (degrees F).
Time frame: single time point
Body composition
Body composition (percent body fat) and bone mineral density by Dual energy X-ray Absorptiometry scan.
Time frame: single time point
Resting and change in metabolism
Resting and postprandial metabolic rates, including respiratory exchange ratios.
Time frame: 0, 0.5, 3, and 6 hours postprandial
Gut microbiota
Gut microbiota composition and gene content will be assessed in stool using polymerase chain reaction (PCR) and sequencing
Time frame: single time point
Gut microbiota fermentation capacity
The fermentation capacity of microbiota will be measured from a single stool sample
Time frame: single time point
Gut microbiota pathogen resistance capacity
The pathogen resistance capability of microbiota will be measured from a single stool sample
Time frame: single time point
Gut inflammation
Gut inflammation will be assessed by measuring molecules in stool and/or the response of intestinal epithelial cell cultures to fecal waters from a single stool sample.
Time frame: single time point
Stool metabolites
Volatile and short chain fatty acids and bile acids will be measured in a single stool sample.
Time frame: single time point
Stool RNA markers
RNA markers will provide a measure of genes expressed by cells of the colon naturally present in a single stool sample
Time frame: single time point
Baseline and change in hunger and appetite
Perceived hunger and fullness will be measured using a visual analog scale. Responses will be a marked on an unsegmented line from 0 or "not at all" to 5 or "extremely."
Time frame: 0, 1, 2, 3, 4, 5, and 6 hours postprandial
Baseline and change in gut fermentation profile
Breath hydrogen and methane measured in response to a challenge meal.
Time frame: 0, 1, 2, 3, 4, 5, and 6 hours postprandial
Recent dietary intake
Random selection of 2 week days and 1 weekend day for 24-hour recall using an automated multi-pass method
Time frame: Three 24-hour dietary recalls collected at home
Dietary intake
Food frequency questionnaire (FFQ)
Time frame: single time point
Behavior assessment
Chronic stress questionnaire, food choice questionnaires, and a food preference activity.
Time frame: single time point
Taste thresholds
Sampling tastes of sweet, salty, and bitter solutions in comparison to water to determine threshold of taste detection.
Time frame: single time point
Skin reflectance
Spectrophotometric measure of skin pigmentation for assessment of vitamin D status.
Time frame: single time point
Peripheral arterial tone
Use of the EndoPAT system to measure blood vessel tone.
Time frame: single time point
Pulmonary function
Forced expiratory lung volume test
Time frame: single time point
Pulmonary inflammation
Pulmonary inflammation measured as exhaled nitric oxide (NO)
Time frame: single time point
Executive function
Executive function will be assessed using Cambridge Neuropsychological Test Automated Battery (CANTAB) and Iowa Gambling Task
Time frame: single time point
Cognitive function
Measured by Wechsler Abbreviated Standard Intelligence test.
Time frame: single time point
Aerobic fitness assessment
Pulse rate (bpm) and recovery after a 3 min YMCA Step Test
Time frame: single time point
Submaximal oxygen consumption
The submaximal volume of oxygen consumed during a 4 minute treadmill walking protocol (VO2max) (ml/kg\*min)
Time frame: single time point
Physical activity
Use of an accelerometer worn on the hip for 7 days
Time frame: daily, for 7 days
Usual physical activity
Activity recall using a questionnaire
Time frame: single time point
Heart rate variability and autonomic nerve conductivity
Monitoring of autonomic balance, cardiac performance, and respiratory measurements and activity using MindWare Mobile Impedance Cardiograph.
Time frame: single time point
Allostatic Load
An aggregate score derived from measures of urinary cortisol, norepinephrine, epinephrine, blood cholesterol, high sensitivity c-reactive protein, and hemoglobin A1C.
Time frame: single time point
Baseline and change in salivary cortisol in response to test meal
Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA)
Time frame: 0, immediately post-prandial, 30, 60, and 90 minutes post-prandial
Baseline and change in salivary cortisol in response to exercise
Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA)
Time frame: 0, immediately post-exercise, 30, 60, and 90 minutes post-exercise
Baseline and change in salivary cortisol in response to emotional recall task
Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA)
Time frame: 0, immediately post-task, 30, 60, and 90 minutes post-task
Baseline and change in breath aldehydes
The concentration of aldehydes present in human breath before and after a high-fat meal will be measured by mass spectrometry
Time frame: 0, 1, 4 and 6 hours postprandial
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